Journal of Diabetes Science and Technology最新文献

{"title":"Diabetes Device Satisfaction Among Adolescents Living With Type 1 Diabetes and Their Parents.","authors":"Jessie J Wong, Selma A Alamarie, Sarah J Hanes, Haley Flores, Jessica Ngo, Aika K Schneider-Utaka, Korey K Hood","doi":"10.1177/19322968241296135","DOIUrl":"10.1177/19322968241296135","url":null,"abstract":"<p><strong>Background: </strong>Diabetes technologies are valuable tools to reduce burden and enhance glycemic control, especially during adolescence. The current study sought to understand the factors associated with parent and adolescent diabetes device satisfaction.</p><p><strong>Methods: </strong>This study used cross-sectional data from 175 adolescents living with type 1 diabetes and 176 parents. Adolescent ages ranged from 12 to 19 (M_age=14.7, SD=1.89) and were balanced by gender (48% male). Kendall's W examined concordance between parent and adolescent satisfaction and bivariate correlations and paired <i>t</i>-tests identified correlates of satisfaction.</p><p><strong>Results: </strong>There was low concordance (Kendall's W = 0.13) between parent and adolescent device satisfaction. Automated insulin delivery (AID) use (vs non-use) was related to higher satisfaction for adolescents (4.52 [0.71] vs 4.20 [0.87], <i>P</i> = .008) and parents (4.25 [0.82] vs 3.71 [0.90], <i>P</i> < .001). Pump use was not significantly related. Parent satisfaction was correlated with hemoglobin A_1c (HbA_1c; R = -0.301, <i>P</i> < .001), percent time-in-range (R = 0.214, <i>P</i> = .007), and percent time-above-range (R = -0.193, <i>P</i> = .015). Adolescent satisfaction was unrelated to glycemic measures. Adolescent and parent satisfaction were both related to better psychosocial functioning. Significant associations between AID use, psychosocial functioning, and glycemic control and device satisfaction remained after accounting for one another. Demographic correlates were non-significant.</p><p><strong>Conclusions: </strong>Adolescents and their parents have discrepant levels of satisfaction with devices. Although both adolescent and parent satisfaction are linked to use of automated technology and better psychosocial functioning, only parent satisfaction is associated with glycemia. This pattern suggests adolescents and parents hold varying priorities when it comes to device use. Acknowledging and addressing these differences may enhance the uptake and continued use of devices.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241296135"},"PeriodicalIF":4.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142621201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying the Relationship Between CGM Time in Range and Basal Insulin Adherence in People With Type 2 Diabetes.","authors":"Jannie Toft Damsgaard Nørlev, Thomas Kronborg, Morten Hasselstrøm Jensen, Peter Vestergaard, Ole Hejlesen, Stine Hangaard","doi":"10.1177/19322968241296828","DOIUrl":"10.1177/19322968241296828","url":null,"abstract":"<p><strong>Background: </strong>The study aimed to determine the relationship between basal insulin adherence and glycemic control evaluated by time in range (TIR) in people with insulin-treated type 2 diabetes (T2D), using data from both continuous glucose monitors (CGM) and connected insulin pens. Furthermore, the study aimed to determine the best basal insulin adherence metric.</p><p><strong>Methods: </strong>CGM data and basal insulin data were collected from 106 insulin-treated people (aged ≥18 years) with T2D. Three different adherence metrics were employed (dose deviation, dose deviation ≤20%, and a traditional metric) and a three-step methodology was used to measure insulin adherence level. The coefficient of determination (R²), based on a univariate linear regression analysis, was used to determine the relationship between each adherence metric and TIR.</p><p><strong>Results: </strong>A statistically significant relationship was observed between TIR and adherence quantified as the dose deviation ≤20% metric (R² = 0.67, <i>P</i> = .006). Neither the relationship between the dose deviation metric and TIR (R² = 0.43, <i>P</i> = .08) nor the relationship between the traditional metric and TIR (R² = 0.35, <i>P</i> =.23) was found to be statistically significant.</p><p><strong>Conclusions: </strong>Our study indicates a relationship between basal insulin adherence and TIR in people with insulin-treated T2D. This seems to underscore the role of basal insulin adherence for optimal glycemic outcomes and utilizing TIR as a clinical marker. Furthermore, the results suggest that the magnitude of deviation from the recommended basal insulin dose impacts glycemic control, indicating dose deviation ≤20% as a more accurate metric for quantifying adherence.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241296828"},"PeriodicalIF":4.1,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571617/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142621217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Importance of Cybersecurity/The Relevance of Cybersecurity to Diabetes Devices: An Update from Diabetes Technology Society.","authors":"Cindy N Ho, Alessandra T Ayers, Rachel E Aaron, Tiffany Tian, Chin-Sean Sum, David C Klonoff","doi":"10.1177/19322968241296543","DOIUrl":"10.1177/19322968241296543","url":null,"abstract":"<p><p>As medical devices become more integrated with wireless technologies, the risks of cyberattacks and data breaches increase, making stringent cybersecurity measures essential. The implementation of rigorous cybersecurity standards is essential for enhancing the cybersecurity of devices. This article examines the evolving cyber threats faced by the medical technology industry, the role of IEEE 2621 in providing comprehensive security benchmarks for medical devices, and the need for continuous risk assessments and adherence to regulatory standards to mitigate future cyber risks. Adherence to cybersecurity standards establishes ensures the effective protection of sensitive data and critical infrastructure.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241296543"},"PeriodicalIF":4.1,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571616/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142604946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effectiveness of Digital Health Lifestyle Interventions on Weight Loss in People With Prediabetes: A Systematic Review, Meta-Analysis, and Meta-Regression.","authors":"Tanja Fredensborg Holm, Flemming Witt Udsen, Iben Engelbrecht Giese, Kristine Færch, Morten Hasselstrøm Jensen, Bernt Johan von Scholten, Stine Hangaard","doi":"10.1177/19322968241292646","DOIUrl":"10.1177/19322968241292646","url":null,"abstract":"<p><strong>Background: </strong>Digital health lifestyle interventions (DHLI) may offer scalable solutions to manage prediabetes in clinical practice; however, their effectiveness on people with prediabetes has not been systematically investigated and reviewed. Hence, in this systematic review, meta-analysis, and meta-regression the effectiveness of DHLI on prediabetes-related outcomes was investigated.</p><p><strong>Methods: </strong>Four databases were searched to identify randomized controlled trials investigating the effectiveness of DHLI on adults with prediabetes published before 23 February 2024. The primary outcome was the change in body weight, with secondary outcomes including, among others, glycemic status, body composition, and feasibility outcomes. Meta-analyses were conducted to provide overall effect estimates of outcomes. In addition, meta-regressions on the primary outcome were conducted. The study quality was assessed using the Cochrane Risk of Bias tool, and the certainty of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.</p><p><strong>Results: </strong>A total of 33 studies were included (n = 14 398). The study duration ranged from 3 to 60 months. The digital interventions varied from in-person meetings combined with pedometers and telephone calls to fully digital interventions. The overall estimated treatment difference in change in body weight favored the intervention (mean difference: -1.74 kg; 95% confidence interval: -2.37, -1.11; <i>P <</i> .01) with moderate certainty. Statistically significant overall effect estimates favoring the intervention were also found for secondary outcomes with very low to moderate certainty.</p><p><strong>Conclusion: </strong>Digital health lifestyle interventions can result in statistically significant change in body weight and other secondary outcomes among people with prediabetes.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241292646"},"PeriodicalIF":4.1,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571619/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142604948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced Glycation End Products (AGEs) Webinar Meeting Report.","authors":"Cindy N Ho, Alessandra T Ayers, Paul Beisswenger, Stuart Chalew, Ann Marie Schmidt, Ambarish Pandey, Pankaj Kapahi, Alexander Fleming, David C Klonoff","doi":"10.1177/19322968241296541","DOIUrl":"10.1177/19322968241296541","url":null,"abstract":"<p><p>The advanced glycation end products (AGEs) Webinar was co-hosted by Diabetes Technology Society and Kitalys Institute on August 8, 2024, with the goal of reviewing progress made in the measurement and use of AGEs in clinical practice. Meeting topics included (1) AGEs as predictors of diabetic nephropathy (DKD), (2) hemoglobin glycation index (HGI) and the glycation gap (GG), (3) formation and structure of AGEs, (4) AGEs as a risk factor of cardiovascular disease (CVD), and (5) approaches to limit or prevent AGE formation.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241296541"},"PeriodicalIF":4.1,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142604945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Older Adults Benefit From Virtual Support for Continuous Glucose Monitor Use But Require Longer Visits.","authors":"Ruth S Weinstock, Dan Raghinaru, Robin L Gal, Richard M Bergenstal, Amy Bradshaw, Terra Cushman, Craig Kollman, Davida Kruger, Mary L Johnson, Teresa McArthur, Beth A Olson, Sean M Oser, Tamara K Oser, Roy W Beck, Korey Hood, Grazia Aleppo","doi":"10.1177/19322968241294250","DOIUrl":"10.1177/19322968241294250","url":null,"abstract":"<p><strong>Background: </strong>Older adults may be less comfortable with continuous glucose monitoring (CGM) technology or require additional education to support use. The Virtual Diabetes Specialty Clinic study provided the opportunity to understand glycemic outcomes and support needed for older versus younger adults living with diabetes and using CGM.</p><p><strong>Methods: </strong>Prospective, virtual study of adults with type 1 diabetes (T1D, N = 160) or type 2 diabetes (T2D, N = 74) using basal-bolus insulin injections or insulin pump therapy. Remote CGM diabetes education (3 scheduled visits over 1 month) was provided by Certified Diabetes Care and Education Specialists with additional visits as needed. CGM-measured glycemic metrics, HbA1c and visit duration were evaluated by age (<40, 40-64 and ≥65 years).</p><p><strong>Results: </strong>Median CGM use was ≥95% in all age groups. From baseline to 6 months, time 70 to 180 mg/dL improved from 45% ± 22 to 57% ± 16%; 50 ± 25 to 65 ± 18%; and 60 ± 28 to 69% ± 18% in the <40, 40-64, and ≥65-year groups, respectively (<40 vs 40-64 years <i>P</i> = 0.006). Corresponding values for HbA1c were 8.0% ± 1.6 to 7.3% ± 1.0%; 7.9 ± 1.6 to 7.0 ± 1.0%; and 7.4 ± 1.4 to 7.1% ± 0.9% (all <i>P</i> > 0.05). Visit duration was 41 min longer for ages ≥65 versus <40 years (<i>P</i> = 0.001).</p><p><strong>Conclusions: </strong>Adults with diabetes experience glycemic benefit after remote CGM use training, but training time for those >65 years is longer compared with younger adults. Addressing individual training-related needs, including needs that may vary by age, should be considered.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241294250"},"PeriodicalIF":4.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571625/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142564567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote Digital Technologies for the Early Detection and Monitoring of Cognitive Decline in Patients With Type 2 Diabetes: Insights From Studies of Neurodegenerative Diseases.","authors":"Ashley Y DuBord, Emily W Paolillo, Adam M Staffaroni","doi":"10.1177/19322968231171399","DOIUrl":"10.1177/19322968231171399","url":null,"abstract":"<p><p>Type 2 diabetes (T2D) is a risk factor for cognitive decline. In neurodegenerative disease research, remote digital cognitive assessments and unobtrusive sensors are gaining traction for their potential to improve early detection and monitoring of cognitive impairment. Given the high prevalence of cognitive impairments in T2D, these digital tools are highly relevant. Further research incorporating remote digital biomarkers of cognition, behavior, and motor functioning may enable comprehensive characterizations of patients with T2D and may ultimately improve clinical care and equitable access to research participation. The aim of this commentary article is to review the feasibility, validity, and limitations of using remote digital cognitive tests and unobtrusive detection methods to identify and monitor cognitive decline in neurodegenerative conditions and apply these insights to patients with T2D.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1489-1499"},"PeriodicalIF":4.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11528805/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9722144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond A1c: Investigating the Contribution of Red Blood Cell Parameters to Dysglycemia Diagnostics.","authors":"Simon Lebech Cichosz","doi":"10.1177/19322968241228541","DOIUrl":"10.1177/19322968241228541","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1519-1520"},"PeriodicalIF":4.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11529149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139545444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rebound Hypoglycemia and Hyperglycemia in Type 1 Diabetes.","authors":"Klavs W Hansen, Bo M Bibby","doi":"10.1177/19322968231168379","DOIUrl":"10.1177/19322968231168379","url":null,"abstract":"<p><strong>Aims: </strong>The aim was to investigate rebound hypoglycemic and hyperglycemic events, and describe their relation to other glycemic metrics.</p><p><strong>Methods: </strong>Data from intermittently scanned continuous glucose monitoring were downloaded for 90 days for 159 persons with type 1 diabetes. A hypoglycemic event was defined as glucose <3.9 mmol/l for at least two 15-minute periods. Rebound hypoglycemia (Rhypo) was a hypoglycemic event preceded by glucose >10.0 mmol/l within 120 minutes and rebound hyperglycemia (Rhyper) was hypoglycemia followed by glucose >10.0 mmol/l within 120 minutes.</p><p><strong>Results: </strong>A total of 10 977 hypoglycemic events were identified of which 3232 (29%) were Rhypo and 3653 (33%) were Rhyper, corresponding to a median frequency of 10.1, 2.5, and 3.0 events per person/14 days. For 1267 (12%) of the cases, Rhypo and Rhyper coexisted. The mean peak glucose was 13.0 ± 1.6 mmol/l before Rhypo; 12.8 ± 1.1 mmol/l in Rhyper. The frequency of Rhyper was significantly (<i>P</i> < .001) correlated with Rhypo (Spearman's rho 0.84), glucose coefficient of variation (0.78), and time below range (0.69) but not with time above range (0.12, <i>P</i> = .13).</p><p><strong>Conclusions: </strong>The strong correlation between Rhyper and Rhypo suggests an individual behavioral characteristic toward intensive correction of glucose excursions.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1392-1398"},"PeriodicalIF":4.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11529140/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9406356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Barriers and Adherence to Insulin Injection Technique in People With Diabetes: Development and Validation of New Assessment Tools.","authors":"Dominic Ehrmann, Bernhard Kulzer, Inka Wienbarg, Jochen Sieber, Siegfried Weber, Thomas Haak, Norbert Hermanns","doi":"10.1177/19322968231175920","DOIUrl":"10.1177/19322968231175920","url":null,"abstract":"<p><strong>Background: </strong>The correct injection technique is crucial for people with insulin therapy. However, barriers to insulin injections exist, which can lead to problems with injections. In addition, injection behavior may deviate from recommendations leading to lower adherence to the correct injection technique. We developed two scales to assess barriers and adherence to the correct technique.</p><p><strong>Methods: </strong>Two item pools were created to assess barriers to insulin injections (barriers scale) and adherence to the correct technique (adherence scale). In an evaluation study, participants completed the two newly created scales, as well as other questionnaires used for criterion validity. Exploratory factor analysis, correlational analysis, and receiver operating characteristics analysis were computed to analyze the validity of the scales.</p><p><strong>Results: </strong>A total of 313 people with type 1 and type 2 diabetes using an insulin pen for insulin injections participated. For the barriers scale, 12 items were selected achieving a reliability of 0.74. The factor analysis revealed three factors namely emotional, cognitive, and behavioral barriers. For the adherence scale, nine items were selected achieving a reliability of 0.78. Both scales showed significant associations with diabetes self-management, diabetes distress, diabetes acceptance, and diabetes empowerment. Receiver operating characteristics analysis showed significant area under the curves for both scales in classifying people with current skin irritations.</p><p><strong>Conclusions: </strong>Reliability and validity of the two scales assessing barriers and adherence to insulin injection technique were demonstrated. The two scales can be used in clinical practice to identify persons in need of education in insulin injection technique.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1362-1369"},"PeriodicalIF":4.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11529062/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9483326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}